Most CEOs talk about AI transformation. John Kim, co-founder and CEO of Sendbird, shows how it’s done. His strategy cuts through the usual platitudes with a blunt truth: if you want your team to use AI, you better be using it more than anyone else. And he’s got the data to prove it.
Key Takeaways
- Sendbird's internal 'Automator' platform and 'AI skills marketplace' lets employees propose 'AI quests' and learn new AI tools.
- Leadership doesn't just preach AI adoption; Sendbird's CTO and co-founder consistently rank as the top AI token consumers.
- The company runs a transparent 'AI token consumption leaderboard,' publicly ranking employees from 'AI newbie' to 'AI god.'
- Sendbird actively identifies and spotlights internal 'champions' already curious about AI, giving them a platform to share their experiments.
Measure What You Model: The AI Token Leaderboard
Forget generic advice about 'leading by example.' Kim’s approach at Sendbird is surgical: they track AI tool usage with an internal 'AI token consumption leaderboard.' Every employee, from new hires to the C-suite, sees where they stand. But the kicker? The leaders aren't just participating; they're dominating.
“The top token consumers in our entire organizations are our CTOs and our my co-founder chief architect,” Kim said. These aren't just figureheads giving lip service. They are actively engaging with the tech, spending the most 'tokens' — Sendbird's internal metric for AI consumption. This isn't just a morale boost; it’s a hard signal that AI isn't optional, and it's something the company's most important people are deeply invested in. It creates a subtle, but powerful, competitive tension that pushes the entire team to explore.
Find Your Internal Champions, Give Them the Mic
Before you roll out some top-down mandate, look around. Kim stresses that AI transformation doesn't begin with a new policy. It starts with people. “There are always people in your organization who are already curious, who already have agency. Find them. Make them the champions. Give them the spotlight.”
At Sendbird, this means empowering those already experimenting with AI. They’ve built tools like the 'Automator,' where anyone can propose an 'AI quest' – a project using AI to solve a specific problem. They also have an 'AI skills marketplace' for learning. By giving these early adopters a platform, Kim turns their individual curiosity into company-wide momentum. These aren’t just employees; they become storytellers, showing colleagues what’s possible and making the intimidating feel accessible.
Build a Culture for 'Failing Forward'
AI is messy. Experimentation often leads to dead ends. Kim understands this isn't a bug, but a feature of rapid progress. He wants his team to embrace failure as a learning opportunity, not a career setback. “This is a beautiful time to fail forward and still get up and run faster than the others,” he explained. This mindset is crucial when you're asking people to experiment with new, often unproven, technologies.
When leaders are actively using AI and transparently ranking high on the token consumption leaderboard, it sends a clear message: taking risks with AI is encouraged. When the co-founder is spending more tokens than an 'AI newbie,' it normalizes the learning curve and implicitly sanctions the idea that you don't have to be perfect from day one. It removes the fear of looking silly or incompetent, making space for genuine discovery.
What to Do With This
This week, track your own AI usage for one day. Note every prompt, every tool, every minute. Then, share your personal AI 'token consumption' with your team, publicly. Challenge your most senior leader to do the same, making their usage visible. This simple act of transparency and personal modeling will spark more experimentation than any top-down memo ever could.